In wireless transmission systems such as orthogonal frequency division multiplexed (OFDM) and orthogonal frequency division multiple access (OFDMA) transmission systems, as well as single-carrier frequency division multiple access (SC-FDMA) transmission systems, an available carrier frequency band is divided into multiple smaller sub-carrier frequency bands. Multiple signals may then be modulated onto these sub-carrier frequency bands and simultaneously transmitted over the available carrier frequency band.
Ideally, the signal received by a receiver matches the transmitted signal. However, in real communication channels, such as a wireless transmission channels, the received signal will vary based on the particular propagation properties of the communication channel, such as the presence of signal interference and multipath reflections. Accordingly, in many OFDM systems, the receiver will perform a channel estimation process to determine the effect that the channel has on a received signal. From such a channel estimation, the receiver is then able to determine how to compensate the received signal for channel fading etc. in order to retrieve the proper shape of the originally transmitted signal.
One way in which this channel estimation may be accomplished is for the receiver to know in advance the ‘modulation’ shape of at least part of a transmitted signal. However, transmitted data is typically random and unpredictable, and so is not suitable for this purpose. One solution is to embed a known symbol pattern (often referred to as a pilot sequence) into the transmitted signal. In this manner, by examining the effect of the channel on this embedded known symbol pattern within the received signal, the receiver may be able to estimate an effect of the communication channel on the rest of the received signal, thereby allowing it to determine how to compensate for the communication channel effect.
FIG. 1 illustrates an example of a block diagram of a known channel estimation circuit 100 for an OFDM receiver. The channel estimation circuit 100 receives as an input a demodulation reference signal (DMRS) 110 comprising a pilot signal in a form of a known reference symbol modulated onto a sub-carrier signal. IDFT circuitry 120 transforms the modulated DMRS signal 110 into the time domain. Filter circuitry 130 then performs a filtering operation on the time domain signal to filter out noise from the pilot signal, and thereby improve the accuracy of the channel estimation signal. DFT circuitry 140 then transforms the filtered time domain signal back into the frequency domain to generate a channel estimation signal 150.
A problem with performing such DFT based channel estimation on a pilot sequence is an effect known as the “edge effect”, whereby after filtering is performed in the time domain, for example by the filter circuitry 130, when the signal is transformed back into the frequency domain using a DFT, for example by the DFT circuitry 140, the estimated communication channel information exhibits high Mean Square Error (MSE) at the edges of the frequency domain signal. This undesirable phenomenon increases with the allocation size. FIG. 2 illustrates an example of a plot of the MSE for a traditional frequency domain channel estimation approach 210 and a plot of the MSE for a typical DFT-based channel estimation approach 220. As illustrated, whilst the DFT-based channel estimation approach 220 performs adequately within the central region of the allocation, the MSE at each edge of the plot for the DFT-based channel estimation approach 220 is very poor, and significantly worse than that for the traditional frequency domain channel estimation approach 210.